November 29, 2018
2 months, online
6-8 hours per week
Note: This online program requires no prerequisites in terms of math or computational sciences, although some experience with introductory-level statistics is helpful.
It’s a common challenge for decision makers: how do we make optimal choices with so many unknown variables? It turns out that business insights come from turning what is unknown into what is known. Using the tools and techniques that facilitate that process is how machine learning can deliver tremendous impact to your organization.
Corporate spending on AI and ML is forecast to grow from $12 billion in 2017 to $57.6 billion by 2021.
SOURCE: INTERNATIONAL DATA CORPORATION
61% of organizations picked machine learning/artificial intelligence as their company’s most significant data initiative for the next year.
SOURCE: MEMSQL SURVEY, 2018
The number of machine learning pilots and implementations will double in 2018 compared to 2017, and double again by 2020.
SOURCE: DELOITTE GLOBAL
This online program takes a look at machine learning through a lens of practical applications. It is designed specifically for decision makers who want to develop a competitive edge by turning what is unknown into what's known—leading to better business decisions and outcomes.
The tools and techniques in this machine learning program can help to address many common business challenges. Learn with examples from:
BANKING: How do you predict whether a borrower will default on a loan?
PHARMACEUTICAL: When developing new drugs, how can you design better experiments to know if a new drug will be more effective than an existing one?
MARKETING: How do you know which marketing channel is performing best, and what is the interaction effect when you are using multiple channels?
RETAIL: To optimize your inventory, how do you know whether to pull from a distribution center or a retail store to fulfill an online order?
FINANCE: How are data scientists exploring ways to predict the future price of digital assets, such as Bitcoin?
ECOMMERCE: How do you decide when to cross-market vs. upsell a customer at checkout—what’s drives more revenue?
Devavrat Shah is a professor with the department of electrical engineering and computer science, MIT. He is a member of the Laboratory for Information and Decision Systems (LIDS) and Operations Research Center (ORC), and the Director of the newly formed Statistics and Data Center in Institute for Data, Systems, and Society. His research focus is on theory of large complex networks, which includes network algorithms, stochastic networks... More info
Get recognized! Upon successful completion of the program, MIT Professional Education grants a certificate of completion to participants. This program is graded as a pass or fail; participants must receive 80% to pass and obtain the certificate of completion.EARN CERTIFICATE
It’s said that studying with MIT is like drinking from a fire hose—intense, yet thirst-quenching. For those participants who demonstrate leadership by going above and beyond in the program, they’ll receive the coveted Fire Hydrant Award. This award can be displayed in professional bios, such as on LinkedIn. Decisions are made by MIT program faculty and facilitators based on participation and behaviors that exemplify exceptional leadership and contribution to the overall program experience for the cohort.
Note: After successful completion of the program, your verified digital certificate will be emailed to you in the name you used when registering for the program. All certificate images are for illustrative purposes only and may be subject to change at the discretion of MIT Professional Education.